Using all data to generate decision tree ensembles. - Gonzalo Martínez-Muñoz; Alberto Suárez 001 (IEEE Trans. Syst. Man Cybern. Part C, 2004)

Switching class labels to generate classification ensembles. - Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Pattern Recognit., 2005)

Building Ensembles of Neural Networks with Class-Switching. - Gonzalo Martínez-Muñoz; Aitor Sánchez-Martínez; Daniel Hernández-Lobato; Alberto Suárez 001 (ICANN (1), 2006)

Pruning in ordered bagging ensembles. - Gonzalo Martínez-Muñoz; Alberto Suárez 001 (ICML, 2006)

Evaluation of Decision Tree Pruning with Subadditive Penalties. - Sergio García-Moratilla; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (IDEAL, 2006)

Pruning in Ordered Regression Bagging Ensembles. - Daniel Hernández-Lobato; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (IJCNN, 2006)

Selection of Decision Stumps in Bagging Ensembles. - Gonzalo Martínez-Muñoz; Daniel Hernández-Lobato; Alberto Suárez 001 (ICANN (1), 2007)

Out of Bootstrap Estimation of Generalization Error Curves in Bagging Ensembles. - Daniel Hernández-Lobato; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (IDEAL, 2007)

Using boosting to prune bagging ensembles. - Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Pattern Recognit. Lett., 2007)

Class-switching neural network ensembles. - Gonzalo Martínez-Muñoz; Aitor Sánchez-Martínez; Daniel Hernández-Lobato; Alberto Suárez 001 (Neurocomputing, 2008)

Dictionary-free categorization of very similar objects via stacked evidence trees. - Gonzalo Martínez-Muñoz; Natalia Larios Delgado; Eric N. Mortensen; Wei Zhang 014; Asako Yamamuro; Robert Paasch; Nadia Payet; David A. Lytle; Linda G. Shapiro; Sinisa Todorovic; Andrew Moldenke; Thomas G. Dietterich (CVPR, 2009)

Statistical Instance-Based Ensemble Pruning for Multi-class Problems. - Gonzalo Martínez-Muñoz; Daniel Hernández-Lobato; Alberto Suárez 001 (ICANN (1), 2009)

Statistical Instance-Based Pruning in Ensembles of Independent Classifiers. - Daniel Hernández-Lobato; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2009)

An Analysis of Ensemble Pruning Techniques Based on Ordered Aggregation. - Gonzalo Martínez-Muñoz; Daniel Hernández-Lobato; Alberto Suárez 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2009)

Haar Random Forest Features and SVM Spatial Matching Kernel for Stonefly Species Identification. - Natalia Larios; Bilge Soran; Linda G. Shapiro; Gonzalo Martínez-Muñoz; Junyuan Lin; Thomas G. Dietterich (ICPR, 2010)

A Double Pruning Algorithm for Classification Ensembles. - Víctor Soto; Gonzalo Martínez-Muñoz; Daniel Hernández-Lobato; Alberto Suárez 001 (MCS, 2010)

Out-of-bag estimation of the optimal sample size in bagging. - Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Pattern Recognit., 2010)

A comparison of techniques for robust gender recognition. - Richard N. Rojas-Bello; Luis Fernando Lago-Fernández; Gonzalo Martínez-Muñoz; Manuel A. Sánchez-Montañés (ICIP, 2011)

Empirical analysis and evaluation of approximate techniques for pruning regression bagging ensembles. - Daniel Hernández-Lobato; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Neurocomputing, 2011)

Inference on the prediction of ensembles of infinite size. - Daniel Hernández-Lobato; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Pattern Recognit., 2011)

On the Independence of the Individual Predictions in Parallel Randomized Ensembles. - Daniel Hernández-Lobato; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (ESANN, 2012)

Evaluation of Negentropy-based Cluster Validation Techniques in Problems with Increasing Dimensionality. - Luis Fernando Lago-Fernández; Gonzalo Martínez-Muñoz; Ana M. González; Manuel A. Sánchez-Montañés (ICPRAM (1), 2012)

How large should ensembles of classifiers be? - Daniel Hernández-Lobato; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Pattern Recognit., 2013)

Improving the Robustness of Bagging with Reduced Sampling Size. - Maryam Sabzevari; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (ESANN, 2014)

Cluster validation in problems with increasing dimensionality and unbalanced clusters. - Luis Fernando Lago-Fernández; Jesús Aragón; Gonzalo Martínez-Muñoz; Ana M. González; Manuel A. Sánchez-Montañés (Neurocomputing, 2014)

A Double Pruning Scheme for Boosting Ensembles. - Víctor Soto; Sergio García-Moratilla; Gonzalo Martínez-Muñoz; Daniel Hernández-Lobato; Alberto Suárez 001 (IEEE Trans. Cybern., 2014)

Using a SPOC to flip the classroom. - Gonzalo Martínez-Muñoz; Estrella Pulido (EDUCON, 2015)

Special Issue on "Solving complex machine learning problems with ensemble methods". - Daniel Hernández-Lobato; Ioannis Katakis 001; Gonzalo Martínez-Muñoz; Ioannis Partalas (Neurocomputing, 2015)

Small margin ensembles can be robust to class-label noise. - Maryam Sabzevari; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Neurocomputing, 2015)

An urn model for majority voting in classification ensembles. - Víctor Soto; Alberto Suárez 001; Gonzalo Martínez-Muñoz (NIPS, 2016)

Analysing Event Transitions to Discover Student Roles and Predict Grades in MOOCs. - Ángel Pérez-Lemonche; Gonzalo Martínez-Muñoz; Estrella Pulido-Cañabate (ICANN (2), 2017)

Randomization vs Optimization in SVM Ensembles. - Maryam Sabzevari; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (ICANN (2), 2018)

Using Bag-of-Little Bootstraps for Efficient Ensemble Learning. - Pablo de Viña; Gonzalo Martínez-Muñoz (ICANN (1), 2018)

Pooling homogeneous ensembles to build heterogeneous ensembles. - Maryam Sabzevari; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (CoRR, 2018)

A two-stage ensemble method for the detection of class-label noise. - Maryam Sabzevari; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Neurocomputing, 2018)

Vote-boosting ensembles. - Maryam Sabzevari; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Pattern Recognit., 2018)

Sequential Training of Neural Networks with Gradient Boosting. - Gonzalo Martínez-Muñoz (CoRR, 2019)

A Comparative Analysis of XGBoost. - Candice Bentéjac; Anna Csörgo; Gonzalo Martínez-Muñoz (CoRR, 2019)

Identifying Cheating Users in Online Courses. - Vicenzo Abichequer Sangalli; Gonzalo Martínez-Muñoz; Estrella Pulido-Cañabate (EDUCON, 2020)

A comparative analysis of gradient boosting algorithms. - Candice Bentéjac; Anna Csörgo; Gonzalo Martínez-Muñoz (Artif. Intell. Rev., 2021)

Multioutput Regression Neural Network Training via Gradient Boosting. - Seyedsaman Emami; Gonzalo Martínez-Muñoz (ESANN, 2022)

SVM Ensembles on a Budget. - David Nevado; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (ICANN (4), 2022)

Building heterogeneous ensembles by pooling homogeneous ensembles. - Maryam Sabzevari; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Int. J. Mach. Learn. Cybern., 2022)

Correction to: Building heterogeneous ensembles by pooling homogeneous ensembles. - Maryam Sabzevari; Gonzalo Martínez-Muñoz; Alberto Suárez 001 (Int. J. Mach. Learn. Cybern., 2022)

An analysis of heuristic metrics for classifier ensemble pruning based on ordered aggregation. - Amgad M. Mohammed; Enrique Onieva; Michal Wozniak 001; Gonzalo Martínez-Muñoz (Pattern Recognit., 2022)

Multi-Task Gradient Boosting. - Seyedsaman Emami; Carlos Ruiz Pastor; Gonzalo Martínez-Muñoz (HAIS, 2023)

Sequential Training of Neural Networks With Gradient Boosting. - Seyedsaman Emami; Gonzalo Martínez-Muñoz (IEEE Access, 2023)

A Gradient Boosting Approach for Training Convolutional and Deep Neural Networks. - Seyedsaman Emami; Gonzalo Martínez-Muñoz (CoRR, 2023)

Deep Learning for Multi-Output Regression Using Gradient Boosting. - Seyedsaman Emami; Gonzalo Martínez-Muñoz (IEEE Access, 2024)

Feature importance analysis for a highly unbalanced multiple myeloma data classification. - Rima Guilal; Nesma Settouti; Gonzalo Martínez-Muñoz; Mohammed Amine Chikh (Int. J. Medical Eng. Informatics, 2024)

Video Visualization Profile Analysis in Online Courses. - Gonzalo Martínez-Muñoz; Miguel Ángel Álvarez-Rodríguez; Estrella Pulido-Cañabate (IEEE Trans. Educ., 2024)

Condensed-gradient boosting. - Seyedsaman Emami; Gonzalo Martínez-Muñoz (Int. J. Mach. Learn. Cybern., 2025)

Robust-Multi-Task Gradient Boosting. - Seyedsaman Emami; Gonzalo Martínez-Muñoz; Daniel Hernández-Lobato (CoRR, 2025)